PROPOSAL FOR IMPACT EVALUATION OF GRADUATED LICENSING SYSTEM ON YOUNG DRIVERS IN ONTARIO
Bibliographic record
Abstract
Rationale: Graduated Licensing (GLS) is a program of gradual driving exposure during the first two years of a novice driver’s experience. This proposal introduces a program model by which GLS could be comprehensively evaluated. Methods: A program logic / conceptual framework model was developed, whereby GLS can be evaluated using five steps. First, program implementation was evaluated using focus group methodology. Second and third, knowledge acquisition and resultant driving behaviour were evaluated using data from the Mann et al. and OSDUS surveys. Fourth, ARIMA time series analysis is proposed to evaluate the impact of GLS on both collisions and lastly on young driver injuries. Results: Pilot data suggest that young drivers are aware of GLS restrictions but do not feel deterred from contravention. Students demonstrated an increase in knowledge about GLS but continued to contravene many GLS restrictions. Conclusions: This comprehensive evaluation may help policy makers improve the GLS program, to reduce young driver injuries and death.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".